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To clarify the dosimetric characteristics of a real-time variable shape rubber-containing tungsten (STR) bolus in a clinical plan and investigate the efficacy of the STR bolus in photon radiotherapy for keloids and other superficial tumors. A 5 mm gel bolus or 1 mm STR bolus was placed on a solid water phantom. Tangential irradiation was performed using a TomoTherapy Radixact-X9 and 6 MV X-ray flattening-filter-free beam, and the surface dose was measured with radiochromic film. Clinical-like plans (TomoDirect; TD and TomoHelical; TH) were applied with the same geometry and the dose distributions were measured. The increase in surface dose by the build-up effect and backscatter was 37.7% and 8.0% for the gel bolus, and 40.5% and 26.4% for the STR bolus, respectively. In the TD and TH plans, the increase in surface dose was 27.4% and 48.3% for the gel bolus, and 39.0% and 63.2% for the STR bolus. Similary, changes in the sagittal plane dose were − 3.9% and 6.1% for the gel bolus, and − 6.3% and 6.9% for the STR bolus. The STR bolus effectively increased the surface dose by the build-up effect and backscatter in photon radiotherapy for keloids and other superficial tumors. [ABSTRACT FROM AUTHOR]

Particle size is a critical parameter for calculating the solid phase holdup and settling velocity in pipeline suspensions. However, accurately determining solid holdup remains challenging due to the complexity and variability in multiphase suspensions, especially when the physical size of the suspended particles is unknown. We have developed a novel multi-frequency particle size measurement system that utilizes acoustic backscatter techniques. Furthermore, we propose a new particle size inversion algorithm that integrates Empirical Mode Decomposition (EMD) and the Pearson Correlation Coefficient (PCC) with traditional algorithms. By applying EMD, the raw echo signal is decomposed into Intrinsic Mode Functions (IMFs), allowing for effective noise separation. The PCC is subsequently used to determine correlations between IMFs, improving signal reconstruction accuracy. The minimum concentration gradient continuous inversion algorithm we proposed effectively solves the multi-solution problem of the energy ratio algorithm through the minimum concentration difference method. This algorithm innovatively employs sliding window technology to accurately assess the optimal particle size range of suspended particles in the ultrasonic measurement path. Experimental results indicate that the Mean Absolute Percentage Error (MAPE) for particle diameters in the ranges of 280–350 μm, 450–550 μm, and 760–880 μm are 7.16 %, 3.87 %, and 4.66 %, respectively. This method provides a precise and efficient solution for measuring particle size distribution in underground pipelines, with broad applications in pipeline maintenance, sediment transport modeling, and drainage system design. • A multi-frequency acoustic system was developed for real-time assessment of particle size in urban rainwater pipelines. • EMD and PCC techniques were applied to decouple flow noise, significantly improving echo signal reconstruction accuracy. • A novel algorithm was proposed for particle size assessment in low-concentration suspensions, achieving MAPE below 10%. • The new algorithm reduces particle size inversion time by 67% compared to traditional methods without compromising accuracy. • Ultrasonic measurement reduces MAPE by 13% compared to image recognition techniques in particle size assessment. [ABSTRACT FROM AUTHOR]

In this paper, we proposed the first wireless multiparameter monitoring method for cryogenic environments (−196 ℃). Present-day cryogenic industries implement a large array of wired sensors to monitor key parameters in fabrication processes. The wirings for a large sensor array greatly complicate the monitoring system. We presented the first wireless multiparameter monitoring method for cryogenic environments by making two efforts. First, a novel wireless passive vibration and pressure sensor is developed. We transfer vibrations and pressures to a relative displacement between a magnet and a tunnel magnetoresistor (TMR). This affects the magnetic field at the TMR and changes the TMR's resistance. By integrating the TMR on a backscattering antenna, the antenna's wireless return loss is modulated by both vibrations and pressures. We proposed a decoupling method for simultaneously monitoring vibration and pressure by a single sensor. Second, we demonstrated and evaluated the first wireless multiparameter cryogenic monitoring system. A wireless passive temperature sensor is developed by integrating a resistance temperature detector (RTD) on a backscattering antenna. The developed vibration and pressure sensor and temperature sensor are tuned to separate frequency bands, embedded in cryogenic environments, and calibrated in situ. Vibrations, pressures, and temperatures in cryogenic environments are synchronously obtained by our wireless cryogenic monitoring system, with an accuracy of 80∼90 %. This research provides a wireless option in large-scale automated cryogenic monitoring, thus it is desirable in implementing the Internet of Things in cryogenic industries. [Display omitted] • A novel wireless passive vibration and pressure sensor functional at −196 ℃. • A wireless multiparameter cryogenic monitoring system is demonstrated. • The embedded wireless sensors work independently without power supply. • Synchronous wireless monitoring of vibration, pressure, and temperature at −196 ℃. [ABSTRACT FROM AUTHOR]

To facilitate the conservation of seafloor habitats and planning of offshore activities, there is a growing need for mapping marine benthos in an effective and efficient way. Acoustic data acquired by multi-beam echosounders (MBES) have been extensively used for large-scale and high-resolution seafloor characterization. A deeper understanding of the relationship between backscatter data and sediment compositions can help to identify the benthos occurrence from the MBES data. With two multi-spectral MBES datasets collected near the western Wadden Sea islands in the North Sea, we investigated the potential of mapping marine benthos through backscatter classification. Two unsupervised classification methods, i.e., Bayesian classification, which mainly exploits the backscatter strength from incident angles larger than 20°, and hierarchical clustering of the backscatter strength at different angular ranges, were employed and the results were compared. The classification results from both methods showed a good correspondence with sediment properties such as the median grain size. Moreover, based on a principal component analysis of bottom sample properties, the hierarchical clustering results indicated a better distinction between contributions from the gravel content and benthos occurrence, e.g., sand mason worm density, than Bayesian classification, through involving the backscatter angular variations. Classification for multiple frequencies, on the other hand, showed little difference regarding the relationship with bottom sample properties. Although the backscatter difference between frequencies was also found to positively correlate with certain sample properties, using multi-spectral features for acoustic classification in this study did not reveal additional information compared to single-frequency classification results.

Lidar profiling of the atmosphere provides information on existence of cloud and aerosol layers and the height and structure of those layers. Knowledge of feature boundaries is a key input to assimilation models. Moreover, identifying feature boundaries with minimal latency is essential to impact operational assimilation and real-time decision making. Using advanced convolution neural network algorithms, we demonstrate real-time determination of atmospheric feature boundaries using an airborne backscatter lidar. Results are shown to agree well with traditional processing methods and are produced with higher horizontal resolution than the traditional method. Demonstrated using airborne lidar, the algorithms and process are extendable to real-time generation of data products from a future spaceborne sensor.

We present a 6.5mm3, 10mg, wireless peripheral nerve stimulator. The stimulator is powered and controlled through ultrasound from an external transducer and utilizes a single 750×750×750μm3 piezocrystal for downlink communication, powering, and readout, reducing implant volume and mass. An IC with 0.06mm2 active circuit area, designed in TSMC 65nm LPCMOS process, converts harvested ultrasound to stimulation charge with a peak efficiency of 82%. A custom wireless protocol that does not require a clock or memory circuits reduces on-chip power to 4μW when not stimulating. The encapsulated stimulator was cuffed to the sciatic nerve of an anesthetized rodent and demonstrated full-scale nerve activation in vivo. We achieve a highly efficient and temporally precise wireless peripheral nerve stimulator that is the smallest and lightest to our knowledge.

We present a 6.5mm3, 10mg, wireless peripheral nerve stimulator. The stimulator is powered and controlled through ultrasound from an external transducer and utilizes a single 750×750×750μm3 piezocrystal for downlink communication, powering, and readout, reducing implant volume and mass. An IC with 0.06mm2 active circuit area, designed in TSMC 65nm LPCMOS process, converts harvested ultrasound to stimulation charge with a peak efficiency of 82%. A custom wireless protocol that does not require a clock or memory circuits reduces on-chip power to 4μW when not stimulating. The encapsulated stimulator was cuffed to the sciatic nerve of an anesthetized rodent and demonstrated full-scale nerve activation in vivo. We achieve a highly efficient and temporally precise wireless peripheral nerve stimulator that is the smallest and lightest to our knowledge.

A passive keyless entry and start (PKES) system is an electronic lock for an automobile that provides the great convenience of opening the door when the user is in proximity. However, the system suffers from relay attacks. Recent studies revealed that relayed signals result in valid packets that are sufficient to unlock doors. In particular, the adversary causes proximity errors by injecting a certain time delay before relaying to manipulate the phase rotation in the response signal. To this end, we present a novel relay-resilient proximity detection solution, BackProx, which uses pseudo-random frequency hopping with the assistance of a reference backscattering device. Since the relay adversary transmits the relayed signals from the key fob at long distances, the signals should propagate over longer distances, resulting in inevitable significant phase rotation with different frequencies. Inspired by this finding, BackProx uses an additional backscattering device to ensure the proximity of the key fob using the invariant characteristics of radio frequency signals in the physical layer (i.e., phase rotation). Our evaluation demonstrates the effectiveness of BackProx in resisting three types of relay attacks. The results show that it achieved a 98% true positive rate at close range and a 0.3% false positive rate at long range. [ABSTRACT FROM AUTHOR]

The classical Smagorinsky model's solution is an approximation to a (resolved) mean velocity. Since it is an eddy viscosity model, it cannot represent a flow of energy from unresolved fluctuations to the (resolved) mean velocity. This model has recently been corrected to incorporate this flow and still be well‐posed. Herein we first develop some basic properties of the corrected model. Next, we perform a complete numerical analysis of two algorithms for its approximation. They are tested and proven to be effective. [ABSTRACT FROM AUTHOR]

Soil moisture plays an important role in agriculture, hydrology, plants’ seasonal growth cycle, and their sustainability under climate change. This letter presents a novel method for regional mapping of soil moisture with partial vegetation cover by using dual-polarized Sentinel-1 C-band SAR data. Model-based retrieval of soil moisture from radar backscatter under partial vegetation cover first necessitates the separation of the backscatter of the underlying soil from total radar backscatter and then the implementation of an inversion technique to estimate its soil moisture content from the backscattering coefficient of the underlying soil. The regional mapping of soil moisture was verified with in situ measurements along a climatic gradient (650–100 mm/year) in central Israel. A good agreement between the estimated soil moisture and the measured from ground samples was found, with an $R^{2}$ of 0.793 with an RMSE of 0.047. [ABSTRACT FROM AUTHOR]

The temporal and spatial resolutions of spaceborne lidar are insufficient, and traditional 1064-/532-/355-nm wavelength lidar devices have difficulty in performing horizontal observations in urban areas due to the eye safety problems. Therefore, there is no mature method of horizontal pollution observation that satisfies hyperfine environmental management and control in urban areas. Recently, 1.5- $\mu \text{m}$ eye-safe lidars were used to build a Jinan quantum lidar network (JQLN), which can observe horizontal aerosol pollution with a radius of 6 km and with high spatial and temporal resolutions of 15 m and 8 min, respectively. In this study, sudden particulate matter (PM) pollution occurred in Jinan from February 21 to 22, 2021. Spaceborne lidar was used to perform a large-scale analysis, and the detailed transport path of pollution was measured by lidar. Pollution transport path forecasting within half an hour and 180 km2 was performed. The forecasting results were in good agreement with the 11 national monitoring stations (NMSs) distributed within the region. The forecasting errors were within minutes and hundreds of meters, and the maximum errors of the pollution arrival time and distribution distance were less than 3 min and 200 m, respectively. This study and the JQLN are promising methods for hyperfine environmental management and control in urban areas. [ABSTRACT FROM AUTHOR]

Advances in sonar technology have revolutionized our ability to map the seafloor, however, differences between legacy and modern data pose challenges when analysing multi-source datasets. Acoustic backscatter recorded via multibeam echosounder is commonly used to characterize the seafloor, but a lack of standardized calibration often yields relative rather than absolute backscatter measurements, hindering comparison between surveys. ‘Bulk shift’ methods have been developed for harmonizing legacy backscatter datasets using overlapping survey areas for relative statistical calibration. This becomes increasingly difficult, though, given many datasets collected over extensive time periods. Backscatter data were collected in the Bay of Fundy, Canada, using multiple sonar systems and vessels over an 18-year period. Here, we propose a reproduceable strategy for harmonizing this large volume of disparate backscatter data using the bulk shift method. A final, harmonized map is presented for the entire Bay of Fundy and is validated using in situ observations from seafloor imagery. [ABSTRACT FROM AUTHOR]

Evaluation of crop growth parameters is crucial to understand the crop phenology and its relation with Synthetic Aperture Radar (SAR) scattering mechanism. The study explores the potential of dual polarization Sentinel–1 backscatter parameters to investigate its sensitivity with various biophysical parameters of paddy crop. Temporal profile of crop growth parameters such as fresh biomass, dry biomass, vegetation water content (VWC) and plant height of paddy crop are assessed with respect to SAR parameters such as VV, VH, VH/VV and Radar Vegetation Index (RVI). Temporal Sentinel–1A SAR data during June to November 2018 was considered for this study. Regression analysis using linear and logarithmic models reveal that the sensitivity of Sentinel–1A backscatter parameters with crop biophysical parameters is best when the crop is at early vegetation stage i.e. between tillering to booting stages with maximum R2 value of 0.68 for liner regression with VH and 0.69 for multiple regression for crop height followed by other biophysical parameters. At later vegetation stage i.e. ripening stage maximum R2 value of 0.52 for liner regression with VH and multiple regression for crop biomass is observed. There is no significant correlation for peak vegetation stage. The results are indicative for the potential use of dual-polarimetric SAR parameters as input parameters for multiple regression models to improve the prediction of biophysical parameters at different phenolgical stages. [ABSTRACT FROM AUTHOR]

Forests' ecosystems are an essential part of the global carbon cycle with vast carbon storage potential. These systems are currently under external pressures showing increasing change due to climate change. A better understanding of the biophysical properties of forests is, therefore, of paramount importance for research and monitoring purposes. While there are many biophysical properties, the focus of this study is on the in-depth analysis of the connection between the C-band Copernicus Sentinel-1 SAR backscatter and evapotranspiration (ET) estimates based on in situ meteorological data and the FAO-based Penman–Monteith equation as well as the well-established global terrestrial ET product from the Terra and Aqua MODIS sensors. The analysis was performed in the Free State of Thuringia, central Germany, over coniferous forests within an area of 2452 km2, considering a 5-year time series (June 2016–July 2021) of 6- to 12-day Sentinel-1 backscatter acquisitions/observations, daily in situ meteorological measurements of four weather stations as well as an 8-day composite of ET products of the MODIS sensors. Correlation analyses of the three datasets were implemented independently for each of the microwave sensor's acquisition parameters, ascending and descending overpass direction and co- or cross-polarization, investigating different time series seasonality filters. The Sentinel-1 backscatter and both ET time series datasets show a similar multiannual seasonally fluctuating behavior with increasing values in the spring, peaks in the summer, decreases in the autumn and troughs in the winter months. The backscatter difference between summer and winter reaches over 1.5 dB, while the evapotranspiration difference reaches 8 mm/day for the in situ measurements and 300 kg/m2/8-day for the MODIS product. The best correlation between the Sentinel-1 backscatter and both ET products is achieved in the ascending overpass direction, with datasets acquired in the late afternoon, and reaches an R2-value of over 0.8. The correlation for the descending overpass direction reaches values of up to 0.6. These results suggest that the SAR backscatter signal of coniferous forests is sensitive to the biophysical property evapotranspiration under some scenarios. [ABSTRACT FROM AUTHOR]

We present the design of a passive wireless communication method that does not rely on ambient or generated RF sources. Instead, the method modulates the Johnson (thermal) noise of a resistor to transmit information bits wirelessly. By selectively connecting or disconnecting a matched resistor to an antenna, the system can achieve data rates of up to 26 bps and distances of up to 7.3 m. This communication method operates at very low power, similar to that of an RFID tag, with the advantage of not requiring a preexisting RF signal to reflect. [ABSTRACT FROM AUTHOR]

The low-power radio technologies open up many opportunities to facilitate Internet-of-Things (IoT) into our daily life, while their minimalist design also makes IoT devices vulnerable to many active attacks. Recent advances use an antenna array to extract fine-grained physical-layer signatures to identify the attackers, which adds burdens in terms of energy and hardware cost to IoT devices. In this paper, we present ShieldScatter, a lightweight system that attaches low-cost tags to single-antenna devices to shield the system from active attacks. The key insight of ShieldScatter is to intentionally create multi-path propagation signatures with the careful deployment of tags. These signatures can be used to construct a sensitive profile to identify the location of the signals’ arrival, and thus detect the threat. In addition, we also design a tag-random scheme and a multiple receivers combination approach to detect a powerful attacker who has the strong priori knowledge of the legitimate user. We prototype ShieldScatter with USRPs and tags to evaluate our system in various environments. The results show that even when the powerful attacker is close to the legitimate device, ShieldScatter can mitigate 95 percent of attack attempts while triggering false alarms on just 7 percent of legitimate traffic. [ABSTRACT FROM AUTHOR]

A long-standing vision of backscatter networks is to provide long-range connectivity and high-speed transmissions for batteryless Internet-of-Things (IoT). Recent years have seen major innovations in designing backscatter networks toward this goal. Yet, they either operate at a very short range, or experience extremely low throughput. This paper takes one step further towards breaking this stalemate, by presenting PolarScatter that exploits channel polarization in long-range backscatter networks. We transform backscatter channels into nearly noiseless virtual channels through channel polarization, and convey bits with extremely low error probability. Specifically, we propose a new polar code scheme that automatically adapts itself to different channel quality, and design a low-cost encoder to accommodate polar codes on resource-constrained backscatter tags. Furthermore, we devise a new metric to calculate log-likelihood ratio for accurate decoding, and present a stopping criterion of iterations to reduce decoding latency. We build a prototype PCB tag, and our experiments show that it achieves up to 11.5× throughput improvement over the state-of-the-art long-range backscatter solution. We also simulate an IC design in TSMC 65 nm LP CMOS process. Compared with traditional encoders, our encoder reduces storage overhead by three orders of magnitude, and lowers the power consumption to tens of microwatts. [ABSTRACT FROM AUTHOR]

Self-sustainable energy harvesting for Internet of Things devices is challenging since ambient energy may be sporadic and unpredictable. This situation leads to frequent power failures that lead to intermittent operations, which prevent the reliability of data communications. This article presents fundamental hardware circuitry that enables reliable intermittent communications over wireless batteryless node networks. We emphasize two main mechanisms that ensure energy awareness and reliability: energy status-sharing and synchronized operation. We introduce novel low-power and self-sustainable plug-and-play circuits to support these mechanisms. [ABSTRACT FROM AUTHOR]

Abstract Due to the high‐speed rotors and overlapped propellers, it is still a challenge to extract the micro‐motion parameters of the quadcopter. In this work, the authors establish a radar backscattering model of the quadcopter based on the flight control theory and radar backscattering characteristics. Then, the improved template matching method and peak grouping method are proposed to capture the periodic information for overlapped propellers on a range‐time profile and extract the rotation speeds of rotors. By simulating the nine types of quadcopter movements, the relative error of the rotation speeds is estimated to be lower than 1.4% for each rotor with a signal‐to‐noise ratio of 15 dB.

We investigated the possibilities of improving hydrological simulations by assimilating radar backscatter observations from the advanced scatterometer (ASCAT) in the hydrological model SCHEME using a calibrated water cloud model (WCM) as an observation operator. The WCM simulates backscatter based on soil moisture and vegetation data and can therefore be used to generate observation predictions for data assimilation. The study was conducted over two Belgian catchments with different hydrological regimes: the Demer and the Ourthe catchment. The main differences between the two catchments can be summarized in precipitation and streamflow levels, which are higher in the Ourthe. The data assimilation method adopted here was the ensemble Kalman filter (EnKF), whereby the uncertainty of the state estimate was described via the ensemble statistics. The focus was on the optimization of the EnKF, and possible solutions to address biases introduced by ensemble perturbations were investigated. The latter issue contributes to the fact that backscatter data assimilation only marginally improves the overall scores of the discharge simulations over the deterministic reference run, and only for the Ourthe catchment. These performances, however, considerably depend on the period considered within the 5 years of analysis. Future lines of research on bias correction, the data assimilation of soil moisture and backscatter data are also outlined. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT), a key enabler of Agriculture 4.0, has numerous devices and sensors connected to the Internet. Most devices and sensors being powered by batteries with finite capacities may suffer from a limited lifetime. Furthermore, passive devices, such as radio frequency identification (RFID) tags, are expected to be connected. To this end, backscatter communication (BackCom) can play a crucial role in extending the lifetime of devices with limited power sources or supporting the connectivity to passive devices. In this article, we review the application of index modulation (IM) to BackCom. In particular, we discuss the different energy harvesting mechanisms, reliable detection, and security schemes suitable for a low-power wireless communication paradigm. In addition, a detailed review and comparison of existing techniques from recent literature are presented. After reviewing the key potential features of BackCom to support future wireless communication, this article discusses the opportunities of using IM in BackCom. Its focus is mainly on the various existing work that implements IM technologies to reduce energy consumption and enhance spectral and energy efficiencies. Finally, the potential challenges and future research direction in implementing IM for low-power wireless communication systems are presented. [ABSTRACT FROM AUTHOR]

In this paper, we study a novel reconfigurable intelligent surface (RIS) enabled symbiotic radio system, where a RIS is used to enhance the communication between the primary transmitter (PTx) and the primary receiver (PRx), and concurrently transmit its information (e.g., environmental monitoring information) to the PRx by varying the phase shifts. The objective is to cooperatively optimize the active transmit beamforming at the PTx and passive reflecting beamforming at the RIS to minimize the PTx's transmit power, subject to the signal-to-noise ratio constraints of primary and RIS transmissions. A new optimization problem is formulated where the RIS phase shifts are not only related to the channel state information (CSI), but also related to its message. First, we consider the perfect CSI setup to draw useful insights into the cooperative beamforming design between the PTx and RIS. Then, the worst-case robust beamforming design is carried out under the imperfect CSI setup. In particular, we take into account the imperfect successive interference cancellation at the PRx. Finally, simulation results show the effectiveness of the RIS information transfer and the integration of RIS into a symbiotic radio system can significantly improve the performance. [ABSTRACT FROM AUTHOR]

Mutualistic cooperative ambient backscatter communications (AmBC) have been proposed to improve the spectrum and energy efficiencies of Internet-of-Things (IoT) systems, where a primary link (from a primary transmitter to a primary receiver) and an AmBC link (from an IoT device to the same primary receiver) form a mutualism relationship. We note that hardware impairments (HIs), which are unavoidable in practical systems and may significantly affect the transmission rates of the primary and AmBC links and their mutualism relationships, have been largely ignored in the study of mutualistic cooperative AmBC networks. In this paper, we study a mutualistic cooperative AmBC network with HIs at all the active transceivers and a non-linear energy harvesting circuit at each IoT device. We derive closed-form rate expressions for both the AmBC and primary links and theoretically prove that the mutualism relationship between the AmBC and primary links is maintained under HIs, i.e., the rate of the primary link in the mutualistic cooperative AmBC network is still higher than that without the AmBC link. To maximize the weighted sum rate of all links in a cooperative AmBC network under HIs, we propose two resource allocation schemes for two scenarios with a single link and multiple AmBC links, respectively. For the single AmBC link case, we derive the optimal transmit power of the primary transmitter and the optimal power reflection coefficient of the IoT device in closed forms. For the scenario with multiple AmBC links, the weighted-sum-rate maximization problem is transformed into a convex one and solved with convex optimization tools. Computer simulations validate our theoretical results and that our proposed schemes outperform the benchmark schemes in terms of the weighted sum rate. [ABSTRACT FROM AUTHOR]

This article presents the design and experimental characterization of microwave structures based on parity time-reversal duality symmetric bifilar edge waveguides (PTD-BEWs) realized through a parallel plate waveguide (PPW) loaded by a metasurface. The analyzed structures include transmission lines with bends and multiple line arrangements. Due to their unique symmetry properties, these structures are robust against backscattering, thus resembling the behavior of topological WGs, despite the fact they are reciprocal. This makes it possible to guide the electromagnetic (EM) waves along the edge with low insertion losses and unique matching properties. Measurements, performed in the frequency range between 24 and 32 GHz, have confirmed the feasibility of the theoretical concept. [ABSTRACT FROM AUTHOR]

Automotive-Industry 5.0 will use emerging 6G communications to provide robust, computationally intelligent, and energy-efficient data sharing among various onboard sensors, vehicles, and other intelligent transportation system entities. Nonorthogonal multiple access (NOMA) and backscatter communications are two key techniques of 6G communications for enhanced spectrum and energy efficiency. In this article, we provide an introduction to green transportation and also discuss the advantages of using backscatter communications and NOMA in Automotive Industry 5.0. We also briefly review the recent work in the area of NOMA empowered backscatter communications. We discuss different use cases of backscatter communications in NOMA-enabled 6G vehicular networks. We also propose a multicell optimization framework to maximize the energy efficiency of the backscatter-enabled NOMA vehicular network. In particular, we jointly optimize the transmit power of the roadside unit and the reflection coefficient of the backscatter device in each cell, where several practical constraints are also taken into account. The problem of energy efficiency is formulated as nonconvex, which is hard to solve directly. Thus, first, we adopt the Dinkelbach method to transform the objective function into a subtractive one, then we decouple the problem into two subproblems. Second, we employ dual theory and KKT conditions to obtain efficient solutions. Finally, we highlight some open issues and future research opportunities related to NOMA-enabled backscatter communications in 6G vehicular networks. [ABSTRACT FROM AUTHOR]

The results of synchronous remote (lidar) and direct (balloon) measurements of tropospheric and stratospheric aerosol parameters carried out in Tomsk on January 27–30, 2022 are presented. The objective of the experiment was to work off coupled lidar-balloon observations and to validate aerosol backscatter profiles in the upper troposphere and the stratosphere for developing an all-weather system for lidar-balloon monitoring of spatiotemporal and microphysical aerosol characteristics. A good consistency of the retrieved profiles of the backscatter ratio was demonstrated for the close wavelengths (528 and 532 nm for the aerosol backscatter sonde and the lidar, respectively). The possibility of expanding two-wave (353 and 532 nm) lidar observations with an additional wavelength set (470, 850, 940 nm) of the optical balloon aerosol sonde was shown for retrieving the microphysical aerosol parameters during coupled lidar-balloon experiments. [ABSTRACT FROM AUTHOR]

Numerous filamentous fungal species are extensively studied due to their role as model organisms, workhorses in biotechnology, or as pathogens for plants, animals, and humans. Growth studies are mainly carried out on solid media. However, studies concerning gene expression, biochemistry, or metabolism are carried out usually in liquid shake conditions, which do not correspond to the growth pattern on solid media. The reason for this practice is the problem of on-line growth monitoring of filamentous fungal species, which usually form pellets in liquid shake cultures. Here, we compared the time-consuming and tedious process of dry-weight determination of the mold Aspergillus fumigatus with online monitoring of biomass in liquid shake culture by the parallelizable CGQ ("cell growth quantifier"), which implements dynamic biomass determination by backscattered light measurement. The results revealed a strong correlation of CGQ-mediated growth monitoring and classical biomass measurement of A. fumigatus grown over a time course. Moreover, CGQ-mediated growth monitoring displayed the difference in growth of A. fumigatus in response to the limitation of iron or nitrogen as well as the growth defects of previously reported mutant strains (ΔhapX, ΔsrbA). Furthermore, the frequently used wild-type strain Af293 showed largely decreased and delayed growth in liquid shake cultures compared to other strains (AfS77, A1160p+, AfS35). Taken together, the CGQ allows for robust, automated biomass monitoring of A. fumigatus during liquid shake conditions, which largely facilitates the characterization of the growth pattern of filamentous fungal species. [ABSTRACT FROM AUTHOR]

The article discusses promising method of active high-frequency acoustic thermometry, which measures the duration of the backscattering signal of ultrasonic pulses Δt in the upper layer of water-saturated rocks or seabed sediments. An acoustic model is proposed to explain the strong temperature dependence of the duration of this signal in the region of zero and negative temperatures. It is shown that Δt increases with decreasing temperature due to an increase in the reflection coefficient of ultrasonic waves from a layered structure and to a decrease in the absorption coefficient in a water-saturated medium. Field studies carried out on a vast area of the Arctic shelf confirmed the existence of such a dependence. The proposed approach can be effective for remote monitoring of temperature changes in frozen water-saturated rocks on land and in the upper layer of seabed sediments on the shallow Arctic shelf, which is necessary to estimate various environmental risks associated with global warming. [ABSTRACT FROM AUTHOR]

A method for evaluating stratospheric aerosol effects on the stratospheric radiation budget according to balloon sounding with an optical aerosol backscatter probe is presented. It is shown for the sounding in the equatorial zone under conditions of perturbed aerosol filling of the stratosphere that observed changes in the composition of stratospheric aerosol lead to significant changes (2–3-fold) in radiative heating. The evaluation technique is based on using the radiative (line-by-line and Monte Carlo) model of solar radiation transfer and can be especially useful in case of episodical perturbations of the stratospheric aerosol layer resulting from anthropogenic and natural disasters accompanied by aerosol emissions. [ABSTRACT FROM AUTHOR]

This article investigates using optical fibers with enhanced backscattering profiles to improve distributed fiber sensor performance and reduce instrumentation costs. Using a femtosecond (fs) laser direct writing technique, the Rayleigh backscattering profile of a standard telecom fiber was enhanced by more than 40 dB to improve the signal-to-noise ratio (SNR) for optical frequency domain reflectometry (OFDR). The enhanced backscattering signals enable effectively distributed strain measurements using a low-cost tunable laser (TL). Median filtering is applied to denoise cross correlation results to further improve measurement outcomes. Results presented in this article show that a TL with a 1-nm tuning range, which is far less than the tuning range used in commercial OFDR interrogators, can perform effectively distributed strain measurements using sensing fibers with enhanced backscattering profiles. The sensing fiber with over 40-dB backscattering enhancement achieved 4.8-cm spatial resolution in strain measurements with a root mean square accuracy of less than 2.70 $\mu \varepsilon $ when 10–50 $\mu \varepsilon $ were exerted to the sensing fiber. Results presented in this article reveal both the potential and limitations of sensing fibers with enhanced backscattering for OFDR-based distributed fiber sensors. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle (UAV)-enabled backscatter communications (BackComm) is deemed to be a vital technique enabling the data transmission over massive battery-less devices for Internet of Things (IoT). However, the UAV-enabled Backcomm suffers from information leakage due to the broadcasting nature of wireless channels. To cope with the security issue, in this paper, a UAV-enabled multi-user secure BackComm system is developed using analog beamforming (ABF) and randomized continuous wave (RCW) techniques, where the multiple users are supported by the multi-carrier RCW over a single low-complexity radio frequency (RF) chain. By exploiting the RCW transmitted towards backscatter, the eavesdropping link can be eroded without any specific jamming signals. The closed-form of the secrecy rate is studied with the approximations, which is then maximized by jointly optimizing the beamforming together with the UAV’s location and the RCW settings. Simulation results are carried out to confirm the accuracy of the proposed approximation, while the convergence behavior of the optimization algorithm is analyzed. As a result, it can be shown that the secrecy rate can be significantly improved compared with the benchmark schemes. [ABSTRACT FROM AUTHOR]

Heterogeneous backscatter networks are emerging as a promising solution to address the proliferating coverage and capacity demands of next-generation vehicular networks. However, despite its rapid evolution and significance, the optimization aspect of such networks has been overlooked due to their complexity and scale. Motivated by this discrepancy in the literature, this work sheds light on a novel learning-based optimization framework for heterogeneous backscatter vehicular networks. More specifically, the article presents a resource allocation and user association scheme for large-scale heterogeneous backscatter vehicular networks by considering a collaboration centric spectrum sharing mechanism. In the considered network setup, multiple network service providers (NSPs) own the resources to serve several legacy and backscatter vehicular users in the network. For each NSP, the legacy vehicle user operates under the macro cell, whereas, the backscatter vehicle user operates under small private cells using leased spectrum resources. A joint power allocation, user association, and spectrum sharing problem has been formulated with an objective to maximize the utility of NSPs. In order to overcome challenges of high dimensionality and non-convexity, the problem is divided into two subproblems. Subsequently, a reinforcement learning and a supervised deep learning approach have been used to solve both subproblems in an efficient and effective manner. To evaluate the benefits of the proposed scheme, extensive simulation studies are conducted and a comparison is provided with benchmark techniques. The performance evaluation demonstrates the utility of the presented system architecture and learning-based optimization framework. [ABSTRACT FROM AUTHOR]

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Nowadays, Ambient Backscatter Communication (AmBC) systems have emerged as a green communication technology to enable massive self-sustainable wireless networks by leveraging Radio Frequency (RF) Energy Harvesting (EH) capability. A Full-duplex Ambient Backscatter Communication (FAmBC) network with a Full-duplex Access Point (AP), a dedicated Legacy User (LU), and several Backscatter Devices (BDs) is considered in this study. The AP with two antennas transfers downlink Orthogonal Frequency Division Multiplexing (OFDM) information and energy to the dedicated LU and several BDs, respectively, while receiving uplink backscattered information from BDs at the same time. One of the key aims in AmBC networks is to ensure fairness among BDs. To address this, we propose the Multi-objective Lexicographical Optimization Problem (MLOP), which aims to maximize the minimum BD’s throughput while enhancing overall BDs’ throughput, subject to the AP’s subcarrier power, BDs’ reflection coefficients, and backscatter time allocation. Owe to the MLOP is non-convex, we propose Difference Convex Algorithm (DCA) using Exterior Penalty Function Method (EPFM)—an inventive non-convex optimization method— to reach the optimal solution. The most critical advantage of applying this proposed approach is finding the globally optimal solution. The effectiveness of the proposed method supported by theoretical analysis confirms its superiority compared to some of the investigated suboptimal algorithms with the same computational complexity. [ABSTRACT FROM AUTHOR]

In symbiotic radio (SR), a secondary transmitter (STx) transmits messages by modulating its information over the radio frequency (RF) signals received from a primary transmitter (PTx), and in return, the secondary transmission provides multipath gain to the primary transmission. In this paper, we are interested in the fundamental mutualistic mechanism between the primary and secondary transmissions, which describes the condition through which the two systems can benefit each other. Since the symbol period ratio $K$ between secondary and primary transmissions is an important system parameter that affects the mutualistic symbiosis, we first derive the theoretical performance in terms of bit error rate (BER) for both primary and secondary transmissions for arbitrary $K$ by using QPSK modulation scheme at the PTx and BPSK modulation scheme at the STx as an example setup. Then we the obtain closed-form expressions for the condition on $K$ to enable mutualistic symbiosis in SR, which is not related to the specific channel realizations but determined by the average strengths of the direct and backscatter links when the number of receiving antennas is large. Meanwhile, we analyze the average BER performance and the diversity orders for both transmissions in the high signal-to-noise-ratio (SNR) regime. Extensive simulations and numerical results are provided to verify the accuracy of our theoretical analysis and demonstrate the interrelationship between the primary and secondary transmissions. [ABSTRACT FROM AUTHOR]

This study aims at relating the stickiness parameter ($\tau$) of the dense media radiative transfer theory in quasi-crystalline approximation of Mie scattering of densely packed sticky spheres (DMRT-QMS), to the physical parameters of the layered snowpack. A relationship has been derived to express $\tau $ , which modulates the attractive contact force between ice spheres, as a function of ice volume fraction ($\phi $) and coordination number ($n_{c}$). Since $\tau $ is not a measurable parameter, this is a step forward with respect to what is commonly made in the literature, where $\tau $ is assumed as an arbitrary parameter, generally ranging between 0.1 and 0.3, to fit simulated backscattering data with those measured. As a first validation, DMRT-QMS was integrated with the SNOWPACK model to simulate backscattering at X-band (9.6 GHz) driven by nivo-meteorological data acquired on a test area located in Monti Alti di Ornella, Italy. The simulations were compared with Synthetic Aperture Radar COSMO-SkyMed (CSK) satellite observations. The results show a significant agreement ($R^{2} =0.68$), although for a limited dataset of eight points in a unique winter season. [ABSTRACT FROM AUTHOR]

Reactive jammers, which start attacking upon sensing legitimate transmissions, are serious threats to wireless communications. Conventional anti-jamming methods such as frequency hopping-based anti-jamming schemes are not effective against reactive jammers, especially the agile ones that jam immediately after sensing transmissions. Deceiving-based anti-jamming methods have a great potential in harnessing reactive jammers and securing communication channels for legitimate users. However, in deceiving-based anti-jamming methods, reaching the optimal power and channel allocation is complicated due to the unavailability of the jammers’ channel information. In this paper, we propose deceiving-based anti-jamming schemes against reactive jammers employing reinforcement learning. Moreover, we consider both cases where a reactive jammer can jam a channel or all the channels utilized by legitimate users. In the latter case, we model the interaction between users and the jammer as a non-cooperative Stackelberg game and prove equilibrium. In addition, we study different scenarios where the interacting environment is static or dynamic in terms of channel gains. Simulation results show that in static environments, the proposed methods achieve the optimal values of the total received power and Signal-to-interference-plus-noise ratio with an accuracy of 95%. Moreover, in dynamic environments, the proposed methods provide high performance in terms of the considered evaluation metrics. [ABSTRACT FROM AUTHOR]

Backscattering by objects is a relevant phenomenon in millimeter-wave (mm-wave) propagation. Accordingly, computationally efficient models characterizing this process are now available in the literature. However, these models are restricted to single-surface contributions. In this article, we propose a multiple-scattering model for calculating backscattered fields due to consecutive interactions with several smooth electrically-large rectangular surfaces. The model is fundamentally based on the cascading of single-scattering events. In addition, the model is later extended to capture single-scattering blockage between backscattering events. The model is implemented using a Fresnel-integral-based method and validated by means of electromagnetic (EM) simulations and measurements. Furthermore, insight on the effects of the model parameters—number of surfaces, frequency, surface size, surface height-to-width ratio, surface displacement, and antenna-to-surface and surface-to-surface distances—is provided. Due to its computational efficiency, the proposed model can be suitable for system- and link-level simulations of wireless systems, particularly when Monte Carlo simulations are applied. [ABSTRACT FROM AUTHOR]

To solve the problem that a parameter search easily falls into a local optimum and the two-dimensional electron density profile construction error is large in the process of backscatter ionogram inversion, an improved method using neighborhood-aided and multistep fitting is proposed. The ionospheric parameter inversion results in the adjacent space are combined and reconstructed by using the neighborhood-aided correction method. The introduction of auxiliary information sources addresses the defects of the conventional genetic algorithm. The local region multistep fitting method is used to describe the local uniformity and global inhomogeneity of the two-dimensional electron density profile by dividing the fitting region. The experimental results show that the proposed method can improve the accuracy of backscatter ionogram inversion and provide reliable support for tracking radio ray trajectories. [ABSTRACT FROM AUTHOR]

Blockage and backscattering by objects are relevant phenomena in millimeter-wave propagation. Conventionally, these phenomena are treated by means of separate models and, in turn, included in the total channel response. In this letter, we propose a combined model for calculating both blocked and backscattered fields from planar smooth electrically-large rectangular surfaces. The contributions of this letter are twofold: first, a single formulation for calculating both blocked and backscattered fields; and second, backscattering models are proposed for calculating blockage as well. Furthermore, the proposed model can be implemented using several models and, finally, is validated with electromagnetic simulations and measurements. Due to its computational efficiency, the model can be suitable for system- and link-level simulations of wireless systems, particularly when Monte Carlo simulations are applied. [ABSTRACT FROM AUTHOR]

In a backscatter communication system, the backscatter device (BD) transmits its messages to the backscatter receiver (BR) by reflecting the incident signal from an external radio frequency (RF) emitter, instead of using power-hungry active RF components themselves. Thus, backscatter communication has shown great potential for achieving low-power communication. The double-fading effect associated with the backscatter link, however, is a major limiting factor to achieve efficient backscatter communication. Reconfigurable intelligent surfaces (RISs), a recently developed technology, can be applied at the BD to enhance the backscatter link thanks to the fact that both RIS and backscatter communication share the same reflective principle. Such a design can also allow the backscatter communication system to capture the desired RF signal as a reflective carrier in a complex radio environment. In this article, a comprehensive overview of backscatter communication assisted by RIS is given. We first introduce the basics of backscatter communication, which covers the antenna scattering principle, backscatter modulation, and link budget calculation. Then, the details of RIS are discussed, which include antenna-based RIS and metamaterial-based RIS, followed by the discussion of the roles of RIS in backscatter communication. After that, we provide an overview of three types of backscatter communication systems assisted by RIS, including RIS-assisted unmodulated backscatter communication, RIS-assisted ambient backscatter communication, and RIS-assisted symbiotic radio. Emerging applications of these systems, technical challenges, and future opportunities in this emerging field are also presented. [ABSTRACT FROM AUTHOR]

In this letter, we propose a novel communication strategy for Non-orthogonal Multiple Access (NOMA) systems with passive backscattering sensor nodes. The proposed scheme relies on the ability to control the number of backscattering sensors contending the channel, by tuning the transmission power of the illuminator incrementally. Multiple-access interference is then mitigated by Successive Interference Cancellation (SIC) at the receiver. To benchmark the performance of our proposal, a random access NOMA scheme is considered. We show that our proposal outperforms the random access protocol in terms of average spectral efficiency, while guaranteeing a substantial reduction in the energy consumption. [ABSTRACT FROM AUTHOR]

We present a new subgrid stress model for the large eddy simulation of turbulent flows based on the solution of transport equations for stress tensor components. The model was a priori term-by-term calibrated against an open DNS database on forced isotropic turbulence (Johns Hopkins University database). After that, it was applied in a large eddy simulation of non-premixed turbulent combustion. To demonstrate the impact of the new subgrid stress model on scalar fields, we excluded the backward effect of heat release on the subgrid stresses, considering an isothermal reaction (i.e., diluted mixture; the density variations associated with chemical heat release can be neglected) and a Burke–Schumann reaction sheet approximation. A periodic box filled with a homogeneous turbulent velocity field and a three-layer top-hat mixture fraction field was studied. Four simulations were performed in which a fixed model for mixture fraction and its variance was combined with either the proposed subgrid stress model or one of the standard models, including Smagorinsky, dynamic Smagorinsky and WALE. Qualitatively correct backscatter was observed in a simulation with the new model. The differences in the statistics of the mixture fraction and reactive component fields caused by the new subgrid stress model were analyzed and discussed. The importance of using an advanced subgrid stress model was highlighted. [ABSTRACT FROM AUTHOR]

This article proposes a new, nondestructive method for detecting recycled integrated circuits (ICs) using the backscattering side-channel analysis (BSCA). In particular, this article explains the impact that aging has on the backscattering side-channel signal and validates the findings through simulations. Then, a new detection algorithm based on singular value decomposition for distinguishing unaged and aged ICs from their backscattered measurements is presented. The proposed method is then validated in a series of experiments. The results show that the proposed method is effective in detecting recycled ICs after being aged for a small fraction of the IC’s lifetime (roughly 66 days). The experiments also demonstrate the impact that circuit size and complexity have on detection accuracy. [ABSTRACT FROM AUTHOR]

Wirelessly powered backscatter communications (WPBC) is an emerging technology for providing continuous energy and ultra-low power communications. Despite some progress in WPBC systems, resource allocation for multiple devices towards secure backscatter communications (BC) and efficient-energy harvesting (EH) requests a deep-insight investigation. In this paper, we consider a WPBC system in which a full-duplex access point (AP) transmits multi-sinewave signals to power backscatter devices (BDs) and injects artificial noise (AN) to secure their backscatter transmissions. To maximize the minimum harvested energy and ensure fairness and security of all BDs, we formulate an optimization problem by jointly considering the backscatter time, power splitting ratio between multi-sinewave and AN, and signal power allocation. For a single-BD system, we characterize the achievable secrecy rate-energy region with a non-linear energy harvester and propose two algorithms to solve an energy maximization problem. We then analyze the effect of multi-sinewave and AN signals on BD’s secrecy rate and harvested energy through simulations and proof-of-concept experiments. For a multi-BD system, we propose an iterative algorithm by leveraging block successive upper-bound minimization (BSUM) techniques to solve the non-convex problem of fair resource allocation and show its convergence and complexity. Numerical results show the proposed algorithm achieves optimal and equitable harvested energy for all BDs with satisfying the security constraint. [ABSTRACT FROM AUTHOR]

This paper develops a novel framework to defeat a super-reactive jammer, one of the most difficult jamming attacks to deal with in practice. Specifically, the jammer has an unlimited power budget and is equipped with the self-interference suppression capability to simultaneously attack and listen to the transmitter’s activities. Consequently, dealing with super-reactive jammers is very challenging. Thus, we introduce a smart deception mechanism to attract the jammer to continuously attack the channel and then leverage jamming signals to transmit data based on the ambient backscatter communication technology. To detect the backscattered signals, the maximum likelihood detector can be adopted. However, this method is notorious for its high computational complexity and requires the model of the current propagation environment as well as channel state information. Hence, we propose a deep learning-based detector that can dynamically adapt to any channels and noise distributions. With a Long Short-Term Memory network, our detector can learn the received signals’ dependencies to achieve a performance close to that of the optimal maximum likelihood detector. Through simulation and theoretical results, we demonstrate that with our approaches, the more power the jammer uses to attack the channel, the better bit error rate performance the transmitter can achieve. [ABSTRACT FROM AUTHOR]

This article studies the secondary users’ sum-throughput in an in-band full-duplex (I-FD) cognitive wireless powered backscatter communication network. The secondary network consists of a hybrid access point (H-AP) and a finite number of geographically distributed secondary backscatter sensors (SBSs), each capable of using either the conventional or backscatter communication. The secondary network shares the primary network’s spectrum using an underlay spectrum sharing model. In this model, the H-AP and SBSs operate in I-FD mode to achieve improved spectral and time efficiency. Moreover, when an SBS has little available energy, it switches to the low-energy consumption backscatter method instead of the conventional transmission method. The goal is to maximize the sum-throughput of the SBSs. It is shown that such a problem is a convex optimization problem. Closed-form expressions for the optimal allocated time and energy to SBSs are derived and solved via a low complexity and efficient algorithm called joint optimal time and energy allocation (JOTEA). Numerical results illustrate that the JOTEA algorithm achieves a higher sum-throughput than the benchmark equal time allocation method. Furthermore, if the self-interference cancellation circuit considerably cancels self-interference in the H-AP, the I-FD mode achieves a higher sum-throughput performance than that of the half-duplex mode. Moreover, using backscatter communication results in a further increase in the sum-throughput. [ABSTRACT FROM AUTHOR]

The radar on the Global Precipitation Measurement (GPM) mission observes precipitation at 13.6 GHz (Ku-band) and 35.6 GHz (Ka-band) and also receives echoes from the earth’s surface. Statistics of surface measurements for non-raining conditions are saved in a database for later use in estimating the precipitation path-integrated attenuation. Previous work by Meneghini and Jones (2011) showed that while averaging over larger latitude/longitude bins increase the number of samples, it can also increase sample variance due to spatial inhomogeneity in the data. As a result, Meneghini and Kim (2017) proposed a new, adaptive method of database construction, in which the number of measurements averaged depends on the spatial homogeneity. The purpose of this work is to re-visit previous, single-frequency results using dual-frequency data and optimal interpolation (kriging). Results include that (1) temporal inhomogeneity can create similar results as spatial, (2) Ka-band behavior is similar to Ku-band, (3) the Ku-/Ka-band difference has less spatial inhomogeneity than either band by itself, and (4) kriging and the adaptive method can reduce the sample variance. The author concludes that finer spatial and temporal resolution is necessary in constructing the database for single frequencies but less so for the Ku-/Ka-band difference. The adaptive approach reduces sample standard deviation with a relatively modest computational increase.

ObjectiveThe purpose of this study is to explore the diagnostic performance of two investigational quantitative ultrasound (QUS) parameters, attenuation coefficient and backscatter coefficient, in comparison with conventional ultrasound (CUS) and MRI-estimated proton density fat fraction (PDFF) for predicting histology-confirmed steatosis grade in adults with nonalcoholic fatty liver disease (NAFLD).Subjects and methodsIn this prospectively designed pilot study, 61 adults with histology-confirmed NAFLD were enrolled from September 2012 to February 2014. Subjects underwent QUS, CUS, and MRI examinations within 100 days of clinical-care liver biopsy. QUS parameters (attenuation coefficient and backscatter coefficient) were estimated using a reference phantom technique by two analysts independently. Three-point ordinal CUS scores intended to predict steatosis grade (1, 2, or 3) were generated independently by two radiologists on the basis of QUS features. PDFF was estimated using an advanced chemical shift-based MRI technique. Using histologic examination as the reference standard, ROC analysis was performed. Optimal attenuation coefficient, backscatter coefficient, and PDFF cutoff thresholds were identified, and the accuracy of attenuation coefficient, backscatter coefficient, PDFF, and CUS to predict steatosis grade was determined. Interobserver agreement for attenuation coefficient, backscatter coefficient, and CUS was analyzed.ResultsCUS had 51.7% grading accuracy. The raw and cross-validated steatosis grading accuracies were 61.7% and 55.0%, respectively, for attenuation coefficient, 68.3% and 68.3% for backscatter coefficient, and 76.7% and 71.3% for MRI-estimated PDFF. Interobserver agreements were 53.3% for CUS (κ = 0.61), 90.0% for attenuation coefficient (κ = 0.87), and 71.7% for backscatter coefficient (κ = 0.82) (p < 0.0001 for all).ConclusionPreliminary observations suggest that QUS parameters may be more accurate and provide higher interobserver agreement than CUS for predicting hepatic steatosis grade in patients with NAFLD.